Learning from others to create Innovative Data Products (Industry 4.0 series – Part 2)


In part 1 of this series, I concluded that automation is a boon and that there are plenty of opportunities to create new businesses to fill the latent needs that exist in the marketplace. The question is then about the next step that an entrepreneur or existing business owner can take to launch new products and services. Are there known business model patterns and innovation frameworks to generate new data product portfolio? Are there other business models that might help both mature and startup companies create, deliver, and capture value using big data at the core?

In my view point, it goes without saying that innovative, sustainable Big Data Business Models are as pervasive and sought after as they are elusive. But the grounding truth today is that every company is a tech company whether they are a consumer or a producer of data. New business models have emerged in the internet age. Examples of this are the transitions from bookstore to e-books, from record store to streaming services, from yellow pages to marketplace, and from taxi cabs to ride sharing. The Industry 4.0 represents a new level of organization and control of the entire value chain, across the lifecycle of products. It is increasingly geared to individualized customer wishes, encompassing all phases: from the idea and the order to development and production, and from the delivery of a product to the end customer, as well as recycling and related services.

Content and services are the digital assets core to any business. The core assets, generically, can be thought of in terms of Presentation, Logic or Data assets.

  • Presentation assets are the user interface or visual front-end to an application.
  • Logic assets are the algorithms, analytics or services that take data inputs, do some processing and provide a response.
  • Data is the raw content but can also include simple transformations of the content.

Data (Data as a Service), Presentation (Information as a Service), and Logic (Answers as a Service) are three categories of big data business models based on their value propositions and customers. These business models center on companies that have seemingly valuable big data that they want to monetize in some way.  

Apple (40 years old) and Amazon (20 years old) are two large mature companies, for instance, that have vastly different business models. Both companies have built solid business models around big data; both use big data to present to consumers products and services that might be relevant to them. Netflix and Pandora, on the other hand (18 and 15 years old, respectively) are companies that have designed new big data business models around understanding and creating value for customers in ways that seemed like magic at the time.

Value Proposition is the key behind these business models. For every startup that designs and implements what amounts to a simple and effective big data business model, perhaps changing the entire landscape with it, there are hundreds of larger, more mature companies looking for ways to monetize their own big data in the hope that they can capture new revenue streams. For both these types of customers, Large/Mature and Small/Young, different services are being linked together to provide a complete application system. A company does not have to deliver all three assets. Now more and more companies benefit if they focus on their unique value-add. Once core assets are identified, it becomes clearer which complementary assets will be provided by partners.


An Application Programming Interface (API) is a Data Product that unlocks the value of company’s digital assets and expands reach well beyond a website to mobile apps, wearables, partners, developers and more. This greater reach allows partnerships to be leveraged, and creates a multiplier effect for core assets – enabling innovation with completely new business models. This also opens new distribution and solution options and capture more value from assets.

Functionally, there are four types of Application Programming Interfaces and each type of API has different potential business value associated with it. John Musser (VP Tech of Basho Technologies now) details the revenue models for APIs here.

  • The API is the product:  Direct revenue, Pay per transaction, Tiered pricing bands
  • The API projects the product: Reach more places, Provides more pay per transaction, Enables mobile scenarios, Allows deeper integration with other products
  • The API promotes the product: Business development and lead generation, User acquisition, Advertising, Brand promotion, Affiliate programs
  • The API powers and feeds the product: Content acquisition, Partner tie-in, Internal innovation.

The main challenges and drivers in the industrial environment are -

  • Having a shorter time to market: shorter innovation cycles, more complex products, and greater data volumes
  • Increasing flexibility: individualized mass production, volatile markets, high productivity
  • Boosting efficiency: energy efficiency and resource efficiency are critical competition factors

Data Product (API) can drive success in five different ways -

  1. Mobile Enablement
  2. Customer and Partner ecosystem growth
  3. Digital distribution channels
  4. Power new business models
  5. Internal efficiency and innovation

Learning from others and Experimenting to Innovate Business Models

One approach to learning from other companies is called Freshwatching. Freshwatching is a technique from the book Business Model Generation that allows people to quickly understand the big picture of how a company creates, delivers, and captures value. The idea is to create understanding of current value creation by researching other companies and their business models. The Business Model canvas is a tool that companies can use to document existing models or develop new business. The canvas can be used by companies to quickly understand the drivers to step into markets to enhance their profit and gain market share, or define a business models which gives them the opportunity to increase their competitive advantage.

The idea here is to take company’s three core digital assets - Data, Presentation, and Logic - and map them to known business models of freshwatched companies. Business model innovation should follow a search paradigm that creatively experiments and tests hypothesis in the elements of the new design to determine whether a new product or service is commercially viable.  The search paradigm is inherently riskier and more feedback-oriented compared to the execution mindset necessary when optimizing an established business model.  Modern enterprises need to excel at not only improving existing elements of its current business model but inventing entirely new business models whose exact structure and dynamics are emergent.

The grey colored cells in the table below are not the only assets that the company provides, but rather they indicate the most important, or core asset. The remaining two are candidates for complementary partners, even if there may be some level of “co-opetition”.


Beyond just digital innovations, is there an approach to take company’s three core digital assets to generate new business models for Industry 4.0 Internet of Things? Is there a template to systematically think through the physical and digital assets to create connections and insights to deliver the new value propositions? Here is a link to business model template for the Internet of Things where the emerging business landscape has been mapped in a dynamic, online tool which show the vastness, variety and scope of the Internet of Things, with a focus on new initiatives and start-ups. The canvas provides an overview of current activity (350+ initiatives mapped), hotspots and areas of growth across industries that can be used as a starting point for identification of new opportunity spaces for businesses looking to take a fundamental role in the market. IoT canvas splits the model in two streams, the physical and the digital stream.

Internet and API democratization is the cornerstone of Digital Strategy. Opportunities exist for all companies to connect digital and physical products through API. Anyone can spot an opportunity for a new service and with APIs slot it into a bigger framework. This API explosion means it is feasible to create products that meet customer expectations and desires more accurately — for example to meet a use case in a small market niche, to have access to data in a unique context, or to meet customer's’ preference to interact from a smartphone device. Ultimately it provides companies with the flexibility to support existing business models or to design completely new ones.

Building data products can lead to a combination of business benefits that include: additional revenue channels or extension of existing channels, wider reach (e.g., increase of an organization’s brand awareness), external sources of innovation (facilitating the idea of open innovation), and/or an increase in efficiency. With explosion of data products comes the need for operations management. This leads to additional areas where entrepreneurs can add value added services for Automated service brokering, Service Level Agreements, Programmer-less stitching of web services, development of new application categories through integration of devices and services, API search, and marketing to target developers.

Industry 4.0 is here and we understand patterns and business models that can be put into play to build next-generation products. The next step is Operating Model development, a strong architectural foundation to deliver these products. I’m looking forward to sharing more about that in the next post in this series.

Original Post on LinkedIn Pulse